1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
|
//*********************************************************************//
// Author : Asmita Bhar, Kevin George
//*********************************************************************//
function [val] = cvMean(image, varargin)
// Finds mean values in an input
//
// Calling Sequence
// val = cvMean(image);
// val = cvMean(image, name, value,...);
// val = cvMean(image, name, value,c,r); (only when ROI Processing is true)
//
// Parameters
// image : Input image matrix
// Dimension (Output) : Dimension along which the function operates - Row, Column, All or Custom. Default : All
// CustomDimension (Optional) : The integer dimension over which the function calculates the mean. This value cannot exceed the number of dimensions in input. It applies only when 'Dimension' property is set to 'Custom'. Default : 1
// ROIProcessing (Optional) : It applies only when 'Dimension' property is set to 'All'. It calculates the mean within a particular region of the image. Default : false
// c (Optional): vector of y-coordinates of vectices of a rectangle(ROI). Applicable only when 'ROIProcssing' is set to 'true'.
// r (Optional): vector of x-coordinates of vectices of a rectangle(ROI). Applicable only when 'ROIProcssing' is set to 'true'.
// val : Stores the mean value calculated
//
// Description
// The function calculates the mean value in a given image matrix.
//
// Examples
// //Load an image
// I = imread('peppers.png');
// //Calculate the mean (default dimension is 'All')
// val = cvMean(I);
// //Calculate the mean when dimension is 'Row'
// val = cvMean(I,'Dimension','Row');
// //Calculate the mean within a given ROI
// a = [0 100 100 0];
// b = [0 0 100 100];
// val = cvMean(I,'ROIProcessing','true',a,b);
//
// Authors
// Asmita Bhar
// Kevin George
//
[lhs,rhs] = argn(0);
if rhs<1 then
error(msprintf("Not enough input arguments"));
end
if rhs>9 then
error(msprintf("Too many input arguments"));
end
[iRows iCols]=size(image(1))
iChannels = size(image)
dimension = 'All';
customDimension = 1;
roiProcessing = 'false';
flag1=0;
i=1;
while(i<rhs-1)
if strcmpi(varargin(i),'Dimension')==0 then
dimension = varargin(i+1)
if strcmpi(dimension,"Column") & strcmpi(dimension,"Row") &strcmpi(dimension,"All") & strcmpi(dimension,"Custom") then
error(msprintf(" wrong input argument #%d, Dimension not matched",i))
end
i=i+2;
elseif strcmpi(varargin(i),'CustomDimension')==0 then
customDimension = varargin(i+1)
flag1=1;
i=i+2;
elseif strcmpi(varargin(i), 'ROIProcessing')==0 then
roiProcessing = varargin(i+1)
if(roiProcessing=='true') then
c = varargin(i+2);
r = varargin(i+3);
i=i+4;
else
i=i+2;
end
end
end
if (strcmpi(dimension,'Custom') & (flag1==1))
error(msprintf("The CustomDimension property is not relevant in this configuration"));
end
if (strcmpi(dimension,"All") & strcmpi(roiProcessing,'true'))
error(msprintf("ROI Property is not relevant in this configuration"));
end
if(customDimension<1)
error(msprintf("CustomDimension must be greater than or equal to 1"));
end
if(iChannels==1) then
if(customDimension>2)
error(msprintf("CustomDimension cannot be greater than the dimension of the input."));
end
elseif(iChannels==3) then
if(customDimension>3)
error(msprintf("CustomDimension cannot be greater than the dimension of the input."));
end
end
if(iChannels==1)
I = double(image(1));
elseif(iChannels==3)
I1 = double(image(1));
I2 = double(image(2));
I3 = double(image(3));
end
if(roiProcessing=='false') then
if (dimension=='All') then
if(iChannels==1) then
val = mean(I)
elseif (iChannels==3) then
val1 = mean(I1)
val2 = mean(I2)
val3 = mean(I3)
val = mean([val1 val2 val3])
end
end
if (dimension=='Row') then
if(iChannels==1) then
val = mean(I,'c');
elseif(iChannels==3) then
val1 = mean(I1,'c');
val2 = mean(I2,'c');
val3 = mean(I3,'c');
val(:,:,1) = val1;
val(:,:,2) = val2;
val(:,:,3) = val3;
end
end
if (dimension=='Column') then
if(iChannels==1) then
val = mean(I,'r');
elseif(iChannels==3) then
val1 = mean(I1,'r');
val2 = mean(I2,'r');
val3 = mean(I3,'r');
val(:,:,1) = val1;
val(:,:,2) = val2;
val(:,:,3) = val3;
end
end
if (dimension=='Custom') then
if(iChannels==1) then
if(customDimension==1) then
val = mean(I,'r');
elseif(customDimension==2) then
val = mean(I,'c');
end
elseif(iChannels==3) then
if(customDimension==1) then
val1 = mean(I1,'r');
val2 = mean(I2,'r');
val3 = mean(I3,'r');
val(:,:,1) = val1;
val(:,:,2) = val2;
val(:,:,3) = val3;
elseif(customDimension==2) then
val1 = mean(I1,'c');
val2 = mean(I2,'c');
val3 = mean(I3,'c');
val(:,:,1) = val1;
val(:,:,2) = val2;
val(:,:,3) = val3;
elseif(customDimension==3) then
for i=1:iRows
for j=1:iCols
val(i,j)= mean([I1(i,j) I2(i,j) I3(i,j)]);
end
end
end
end
end
end
if(roiProcessing=='true') then
I4 = roipoly(image,c,r);
out = I4;
output = find(out>0);
[rows cols] = size(out);
if(iChannels==1)
ROI = zeros(iRows,iCols);
for i=1:cols
ROI(output(i)) = image(1)(output(i));
end
elseif(iChannels==3)
ROI1 = zeros(iRows,iCols);
ROI2 = zeros(iRows,iCols);
ROI3 = zeros(iRows,iCols);
for i=1:cols
ROI1(output(i)) = image(1)(output(i));
ROI2(output(i)) = image(2)(output(i));
ROI3(output(i)) = image(3)(output(i));
end
ROI = list(ROI1,ROI2,ROI3);
end
if (dimension=='All') then
if(iChannels==1) then
a=ROI;
val = mean(a(find(a>0)));
elseif (iChannels==3) then
a=ROI(1);
b=ROI(2);
c=ROI(3);
val1 = mean(a(find(a>0)));
val2 = mean(b(find(b>0)));
val3 = mean(c(find(c>0)));
val = mean([val1 val2 val3]);
end
end
end
endfunction
|
